Fuel type prediction from mass flow measurements and thermal conductivity sensor

ABSTRACT

The present disclosure provides a method for predicting a fluid type, comprising sensing, by a first sensor, mass flow data of a fluid in an engine, wherein the first sensor operates based on a first fluid property; sensing, by a second sensor, mass flow data of the fluid, wherein the second sensor operates based on a second fluid property; and detecting, by a logic circuit of a controller, a percent difference in the mass flow data provided by the first and second sensors, the percent difference indicating that the fluid is comprised of at least a first fluid type.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a national phase filing of PCT InternationalApplication Serial No. PCT/US2016/031426, filed May 9, 2016, thedisclosure of which is expressly incorporated herein by reference.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to predicting fuel type andcomposition of natural gas fuel and more specifically to an apparatusand methods for predicting the fuel type and composition based on atleast mass flow sensor measurements and thermal conductivity sensormeasurements.

BACKGROUND OF THE DISCLOSURE

Natural gas is a naturally occurring gas mixture that is comprised ofseveral different types of gas. Many natural gas fuel types areprimarily mixtures of varying percent compositions that include gasessuch as: CH₄ (methane), C₃H₈ (propane), C₂H₆ (ethane), C₄H₁₀ (butane),O₂ (oxygen), N₂ (nitrogen), H₂S (hydrogen sulfide), and CO₂ (carbondioxide). There are a variety of professional suppliers of natural gas.In some instances natural gas supplied from these various suppliers mayhave a similar composition but will rarely be entirely the same.Accordingly, with different gas suppliers each supplying natural gas,the exact composition at any natural gas production site will vary amongdifferent regions.

Having information relating to the chemical composition of natural gassupplied by a particular gas source can be valuable for enginemanufacturers and engine control system designers. For example, thefractions of species within certain natural gas supplies have largeimpacts on the knock, NOx, and lean burning limit capability of theengine. Hence, a need exists for an apparatus and method(s) for reliablypredicting fuel type and composition of natural gas fuel provided by thevarious suppliers. Accordingly, the present disclosure provides anapparatus and method(s) for predicting fuel type and composition ofnatural gas based on sensitivities associated with measuring devicescommonly used in vehicle engine applications.

SUMMARY OF THE DISCLOSURE

In one embodiment, the present disclosure provides a fluid typeprediction system, comprising a first sensor that provides a first massflow measurement of a fluid in an engine, wherein the first sensor issensitive to at least a first property of the fluid; and a second sensorthat provides a second mass flow measurement of the fluid, wherein thesecond sensor is sensitive to at least a second property of the fluid; acontroller configured to detect a difference between the first and thesecond mass flow measurements indicating a presence of at least a firstfluid type in the fluid, and to adjust a performance characteristic ofthe engine in response to detecting the difference between the first andthe second mass flow measurements. In one aspect of this embodiment, thesystem is configured to detect a percentage of the first fluid type inthe fluid in response to the difference between the first and the secondmass flow measurements exceeding a threshold difference. In a variant ofthis aspect, the system further comprises a third sensor that provides ameasurement of a characteristic of the fluid, wherein the characteristicindicates a percentage of a second fluid type in the fluid. In a variantof this variant, the percentage of the first fluid type and thepercentage of the second fluid type are used to determine a presence ofa third fluid type in the fluid and to determine a percentage of thethird fluid type in the fluid. In another variant of this variant, thefirst sensor is an orifice delta pressure mass flow sensor, the secondsensor is a hot film mass flow sensor, and the third sensor is a thermalconductivity sensor. In yet another variant of this variant, the fluidis natural gas fuel comprising at least one of methane, propane, carbondioxide, and combinations thereof, and the characteristic of the fluidis a thermal conductivity of the fluid. In yet another aspect, the fluidis natural gas fuel, the first property is molecular weight, and thesecond property is at least one of viscosity and thermal conductivity.In yet another aspect, the system is configured to estimate a percentageof one or more fluid types in the fluid.

In another embodiment, the present disclosure provides a fluid typeprediction system, comprising a controller comprising at least oneprocessor and memory; and a first interface coupled to the controller,the first interface configured to receive parameter signalscorresponding to a mass flow measurement of a fluid in an engine, theparameter signals being provided by at least a first sensor and a secondsensor; wherein the memory comprises instructions that when executed bythe at least one processor causes the controller to detect a differencebetween the mass flow measurement provided by the first sensor and themass flow measurement provided by the second sensor, the differenceindicating the presence of at least a first fluid type in the fluid, andto adjust a performance characteristic of the engine in response todetecting the difference between the mass flow measurements provided bythe first and second sensors. In one aspect of this embodiment, thesystem is configured to detect a percentage of the first fluid type inthe fluid in response to the difference between the mass flowmeasurements provided by the first sensor and the second sensorexceeding a threshold difference. In another aspect, the first sensor issensitive to at least a first property of the fluid and the secondsensor is sensitive to at least a second property of the fluid. In avariant of this aspect, the fluid is natural gas fuel, the firstproperty is molecular weight, and the second property is at least one ofviscosity and thermal conductivity.

In yet another aspect, the controller comprises a second interfaceconfigured to provide control signals to at least the first sensor andthe second sensor to cause the first and second sensors to provide themass flow measurement to the controller. In yet another aspect, thefirst interface receives parameter signals provided by a third sensor,the parameter signals indicating a characteristic of the fluid, whereinthe characteristic indicates a percentage of a second fluid type in thefluid. In a variant of this aspect, the controller uses the percentageof the first fluid type and the percentage of the second fluid type todetermine a presence of a third fluid type in the fluid and to determinea percentage of the third fluid type in the fluid. In another variant ofthis aspect, the first sensor is an orifice delta pressure mass flowsensor, the second sensor is a hot film mass flow sensor, and the thirdsensor is a thermal conductivity sensor.

In yet another embodiment, the present disclosure provides a method forpredicting a fluid type, comprising providing, by a first sensor, a massflow measurement of a fluid in an engine, wherein the first sensor issensitive to at least a first property of the fluid; providing, by asecond sensor, a mass flow measurement of the fluid, wherein the secondsensor is sensitive to at least a second property of the fluid;detecting, by a logic circuit of a controller, a difference between themass flow measurement provided by the first sensor and the secondsensor, the difference indicating a presence of at least a first fluidtype in the fluid; and adjusting, by the logic circuit, a performancecharacteristic of the engine in response to detecting the differencebetween the mass flow measurement provided by the first sensor and thesecond sensor. In one aspect of this embodiment, the method furthercomprises, detecting a percentage of the first fluid type in the fluidin response to the difference in the mass flow measurement provided bythe first sensor and the second sensor exceeding a threshold difference.In a variant of this aspect, the method further comprises, sensing, by athird sensor, a characteristic of the fluid; detecting, based on thecharacteristic, the presence of at least a second fluid type in thefluid; and determining a percentage of the second fluid type in thefluid. In a variant of this variant, the method further comprises, usingthe percentage of the first fluid type and the percentage of the secondfluid type to determine a presence of a third fluid type in the fluidand to determine a percentage of the third fluid type in the fluid. Inanother variant of this variant, the first sensor is an orifice deltapressure mass flow sensor, the second sensor is a hot film mass flowsensor, the third sensor is a thermal conductivity sensor, the firstproperty is molecular weight, and the second property is at least one ofviscosity and thermal conductivity.

In yet another embodiment, the present disclosure provides a fluid typeprediction system comprising a controller comprising at least oneprocessor and memory; and an interface coupled to the controller, theinterface configured to receive parameters indicating a mass flowmeasurement of a fluid in an engine; wherein the memory comprisesinstructions that when executed by the at least one processor causes thecontroller to detect a difference between a mass flow measurementprovided by a first sensor and a mass flow measurement provided by asecond sensor, the difference indicating the presence of at least afirst fluid type in the fluid; and wherein a performance characteristicof the engine is adjusted in response to the controller detecting adifference between the mass flow measurements provided by the first andsecond sensors. In one aspect of this embodiment, the parametersreceived by the interface are provided by at least the first sensor andthe second sensor. In a variant of this aspect, the interface is furtherconfigured to receive a measurement of a characteristic of the fluid,the characteristic indicating a percentage of a second fluid type in thefluid, and the measurement being provided by a third sensor. In avariant of this variant, the first sensor is an orifice delta pressuremass flow sensor, the second sensor is a hot film mass flow sensor, andthe third sensor is a thermal conductivity sensor. In another aspect,the system is configured to at least one of estimate a percentage of oneor more fluid types in the fluid and detect a percentage of the firstfluid type in the fluid in response to the difference between the firstand the second mass flow measurements exceeding a threshold difference.In yet another aspect, the performance characteristic include at leastone of fuel injection timing, air-to-fuel ratio, charge flow rate andquantity, spark ignition timing, and adjusting the operation of one ormore components of the engine.

BRIEF DESCRIPTION OF THE DRAWINGS

The above-mentioned and other features of this disclosure and the mannerof obtaining them will become more apparent and the disclosure itselfwill be better understood by reference to the following description ofembodiments of the present disclosure taken in conjunction with theaccompanying drawings, wherein:

FIG. 1 is a block diagram of an exemplary prior art flow measuringsystem according to an embodiment of the present disclosure;

FIG. 2 is a block diagram of a fluid type prediction system comprisingat least two sensors according to an embodiment of the presentdisclosure;

FIG. 3 is a graph that correlates sensor data to a first fluidpercentage according to an embodiment of the present disclosure;

FIG. 4 is a graph that correlates sensor data to mass flow rate for aplurality of fluid compositions according to an embodiment of thepresent disclosure;

FIG. 5 is a block diagram of a fluid type prediction system comprisingat least three sensors according to an embodiment of the presentdisclosure;

FIG. 6 is a graph that correlates sensor data to a second fluidpercentage according to an embodiment of the present disclosure; and

FIG. 7 is a flow diagram of an exemplary method for predicting a fluidtype according to an embodiment of the present disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS

The embodiments disclosed herein are not intended to be exhaustive or tolimit the disclosure to the precise forms disclosed in the followingdetailed description. Rather, the embodiments were chosen and describedso that others skilled in the art may utilize their teachings. Thefollowing description is merely exemplary in nature and is in no wayintended to limit the various application or uses of the disclosure. Asused herein, the phrase at least one of A, B, and C should be construedto mean a logical (A or B or C), using a non-exclusive logical OR. Itshould be understood that steps within a method may be executed in adifferent order without altering the principles of the presentdisclosure. As used herein, the term determiner, or interpreter mayrefer to an Application Specific Integrated Circuit (ASIC), anelectronic circuit, a processor (shared, dedicated, or group) and memorythat execute one or more software or firmware programs, a combinationallogic circuit, and/or other suitable components that provide thedescribed functionality.

Referring now to FIG. 1, a block diagram of an exemplary prior art flowmeasuring system according to an embodiment of the present disclosure isshown. Flow measuring system 100 (hereinafter “system 100”) generallyincludes fluid or fuel inlet 102, controller 103, first flow sensor 104,air inlet 106, engine 108, exhaust 110, and torque output 112. As shownin the illustrative embodiment of FIG. 1, controller 103 may beelectrically and communicably coupled to first flow sensor 104.Controller 103 is generally configured to provide one or more controlsignals to first flow sensor 104 to cause flow sensor 104 tosense/measure the mass flow of fluid/fuel flowing into engine 108.Likewise, flow sensor 104 may be configured to provide one or moredata/parameter signals to controller 103 that indicate thesensed/measured flow rate of fluid or fuel flowing into engine 108. Flowsensor 104 may be a conventional flow sensor generally known to one ofordinary skill. In one embodiment, flow sensor 104 is a hot film massflow sensor (e.g., Hitachi Gas Mass Flow Sensor) that operates, in part,based on design sensitivities which are responsive to at least a firstfluid property of the fluid being sensed/measured. In variousembodiments of the present disclosure, a fluid property may be any oneof viscosity of the fluid, thermal conductivity of the fluid, or both.The fluid property may also be the molecular weight of the fluid. In oneembodiment, the first fluid property is one of the thermal conductivityof the fluid, the viscosity of the fluid, and/or a combination of boththermal conductivity and viscosity of the fluid. In the presentdisclosure, the thermal conductivity of the fluid may be also describedas a characteristic of the fluid rather than a property of the fluid.Engine 108 generally operates by combusting a fluid mixture comprisingair supplied by air let 106 and fuel supplied by fuel inlet 102 toproduce drive torque 112 for an exemplary vehicle. Exhaust 110 providesa flow path for exhaust gas produced as a result of the combustion ofexemplary fuels such as natural gas, gasoline and diesel.

As discussed above, natural gas fuels tend to vary in compositiondepending on the location of the fuel source. Natural gas fuelsdispensed from a single source location may also vary in compositionover time. Constituent changes in the composition of natural gas fuelsinclude, for example, changes in the amount of methane, propane, andcarbon dioxide present in the fuel. Generally, natural gas fuel typesmay be broken into two segments, either low Methane Number (MN) (e.g.,natural gas blends comprised of propane) or low British Thermal Units(BTUs) (e.g., natural gas blends comprised of diluents such as carbondioxide). Manufacturers of natural gas engines sometimes use methanenumber (MN) or motor octane number (MON) for specification of gasquality requirements. Both the MON and the MN are measures of the knockresistance of the fuel with the difference being the reference fuelsused. As indicated above, systems that can consistently and reliablyprovide information relating to the chemical composition of natural gasfuels supplied by a particular fuel source can be valuable for enginemanufacturers and engine control system designers. For example, asindicated above, the fractions of species within certain natural gasfuel supplies have large impacts on the knock, NOx, and lean burninglimit capability of a natural gas engine, such as engine 108.Accordingly, the present disclosure provides a sensing and measurementsystem and method for detecting and indicating the presence andfraction/percentage of individual gases that comprise natural gas fuelsdispensed at a particular location.

Referring now to FIG. 2, a block diagram of a fluid type predictionsystem comprising at least two sensors according to an embodiment of thepresent disclosure is shown. Flow measuring system 120 (hereinafter“system 120”) generally includes first flow sensor 104, a second flowsensor 105, and a controller 203. Much like flow sensor 104 describedabove, flow sensor 105 may be configured to provide one or moredata/parameter signals to controller 203 that indicate thesensed/measured flow rate of fluid or fuel flowing into engine 108.Similar to flow sensor 104, flow sensor 105 may also be a conventionalflow sensor generally known to one of ordinary skill. In one embodiment,flow sensor 105 is an orifice delta pressure mass flow rate measurementsensor that operates, in part, based on design sensitivities which areresponsive to a second fluid property of the fluid beingsensed/measured. In one aspect of this embodiment, the second fluidproperty is the molecular weight of the fluid. Controller 203 isgenerally configured to provide one or more control signals to at leastone of flow sensor 104 and flow sensor 105 to cause at least one ofsensor 104 and sensor 105 to sense/measure the mass flow of fluid/fuelflowing into engine 108. Likewise, flow sensors 104, 105 may beconfigured to provide one or more data/parameter signals to controller203 that indicate the sensed/measured flow rate of fluid or fuel flowinginto engine 108.

In the illustrative embodiment of FIG. 2, flow sensor 104 of system 120senses, measures and/or provides a mass flow rate measurement of a fluid(fuel) being supplied to engine 108. In one embodiment, sensor 104 is ahot film mass flow sensor that is sensitive to both the thermalconductivity of the fuel and viscosity of the fuel. Sensor 104 isconfigured to provide one or more parameter signals to controller 203that are indicative of the sensed or measured mass flow rate of thesupplied fuel. System 120 further includes flow sensor 105 that providesa mass flow rate measurement of the fluid (fuel) being supplied toengine 108. In this embodiment, sensor 105 is an orifice delta pressuremass flow rate measurement sensor that is sensitive to the molecularweight of the fuel. Sensor 105 is likewise configured to provide one ormore parameter signals to controller 203 that are indicative of thesensed or measured mass flow rate of the supplied fuel.

As described in more detail herein below, controller 203 receivesparameters signals indicative of mass flow rate measurements from eachof sensors 104, 105 and executes, for example, comparator logic todetect/determine a percent difference between the flow rate measurementvalues provided by each of the two sensors 104, 105. According to thepresent disclosure, and as explained further herein, the detectedpercent difference between a mass flow rate measurement provided bysensor 104 and a mass flow rate measurement provided by sensor 105indicates a presence of at least a first fluid type in an exemplarynatural gas fuel composition. In one embodiment, controller 203 mayprovide one or more control signals to engine 108 to adjust at least oneperformance characteristic of engine 108 in response to detecting apresence of the first fluid type in the natural gas fuel. In variousembodiments of the present disclosure, the performance characteristicsinclude, for example, fuel injection timing, air-to-fuel ratio, chargeflow rate and quantity, spark ignition timing, etc. Likewise, in variousembodiments, adjusting the performance characteristics may includeadjusting the operation of one or more components of engine 108.

In various embodiments of the present disclosure, controller 203 mayinclude one or more interpreters and one or more determiners such as,for example, a processor (P) that functionally executes the operationsof controller 203. Controller 203 may be a single device or adistributed device, and the functions of the controller may be performedby hardware and/or as computer instructions on a non-transient computerreadable storage medium. In the illustrative embodiment of FIG. 2,controller 203 is shown as generally including logic/processor (P) andmemory (M). In one embodiment, the logic/processor of controller 203 maybe a microprocessor that includes one or more control algorithms orlogic which are generally operable to control and manage the overalloperation of one or more disclosed systems as well as control/manage theoperation of a plurality of sensing devices coupled to an exemplaryengine or disposed at various locations within an exemplary vehicle. Inone embodiment, the processor P may include one or more microprocessors,microcontrollers, digital signal processors (DSPs), combinations thereofand/or such other devices known to those having ordinary skill in theart that may be configured to process one or more data and/or parametersignals and to provide one or more control signals.

Controller 203 may comprise a plurality of electronic componentsconfigured to receive analogue and/or digital input signals from aplurality of sensors coupled to an exemplary vehicle and to engine 108.In one or more alternative embodiments, system 120 (and system 150described below) may be utilized in a variety of related applicationshaving an engine that operates based on natural gas fuel. For example,in these alternative embodiments, related applications may include powergeneration systems, industrial equipment, and various other systems anddevices which are powered, in part, by one or more natural gas enginessuch as engine 108. Controller 203 may further include a number of inputand output circuits (e.g., interface circuits) adapted for interfacingwith the plurality of sensors. In one embodiment, controller 203 may bea known control unit customarily referred to by those of ordinary skillas an electronic or engine control module (ECM), electronic or enginecontrol unit (ECU) or the like, or may alternatively be a controlcircuit capable of operation as will be described herein. In oneembodiment, memory M includes random access memory (RAM), dynamic randomaccess memory (DRAM), and/or read only memory (ROM) or equivalentsthereof, that store data and programs that may be executed by processorP and that allow controller 203 to communicate with the above-mentionedcomponents to cause one or more systems to perform the functionalitydescribed herein.

As noted briefly above, in certain embodiments, controller 203 includesone or more interpreters and one or more determiners. The descriptionherein including interpreters and determiners emphasizes the structuralindependence of certain aspects of controller 203, and illustrates onegrouping of operations and responsibilities of the controller. Othergroupings that execute similar overall operations are understood withinthe scope of the present disclosure. Interpreters and determiners may beimplemented in hardware and/or as computer instructions on anon-transient computer readable storage medium, and may be distributedacross various hardware or computer based components. Example andnon-limiting implementation elements that functionally execute theoperations of controller 203 include sensors providing any valuedetermined herein, sensors providing any value that is a precursor to avalue determined herein, datalink and/or network hardware includingcommunication chips, oscillating crystals, communication links, cables,twisted pair wiring, coaxial wiring, shielded wiring, transmitters,receivers, and/or transceivers, logic circuits, hard-wired logiccircuits, reconfigurable logic circuits in a particular non-transientstate configured according to a specification, any actuator including atleast an electrical, hydraulic, or pneumatic actuator, a solenoid, anop-amp, analog control elements (springs, filters, integrators, adders,dividers, gain elements), and/or digital control elements.

In various embodiments of the present disclosure, sensors 104, 105 maybe calibrated to provide mass flow rate measurements for a gaseouscomposition that is pure methane or comprised primarily of methane. Asnoted above, natural gas fuel types are primarily mixtures of varyingpercent compositions that include gases such as: CH₄ (methane), C₃H₈(propane), C₂H₆ (ethane), C₄H₁₀ (butane), O₂ (oxygen), N₂ (nitrogen),H₂S (hydrogen sulfide), and CO₂ (carbon dioxide). In variousembodiments, an exemplary natural gas fuel composition includes methane,propane, and carbon dioxide. As also noted above, major constituentvariations in the composition of natural gas fuels include changes inthe amount of methane, propane, and carbon dioxide present in the fuel.Thus, because sensor 104 is sensitive to both the thermal conductivityand viscosity of a particular fluid type and sensor 105 is sensitive tomolecular weight of a particular fluid type, the detected percentdifference between flow rate measurements of each sensor may be used todetect the presence of, for example, carbon dioxide in the natural gasfuel supplied to engine 108. More particularly, because sensors 104, 105are calibrated to provide flow rate measurements for a gaseouscomposition that is pure methane (or primarily methane); each sensor104, 105 will exhibit errors in flow rate measurements of a natural gasfuel composition that is blended with constituents other than methane.In addition to the errors, there will also be a delta (i.e., percentdifference) between the flow rate measurement provide by sensor 104 andthe flow rate measurement provided by sensor 105. The percent differencecan be used to determine one of: 1) the presence of a first fluid typein the natural gas fuel; 2) the presence of second fluid type in thenatural gas fuel; 3) an estimation of the percentage/fraction of thefirst fluid type in the natural gas fuel; 4) and/or an estimation of thepercentage/fraction of the second fluid type in the natural gas fuel.

FIG. 3 is a graph 130 that correlates a percent difference in flow ratemeasurement between sensors 104,105 to an estimation of thepercentage/fraction of the first fluid type in a natural gas fuelaccording to an embodiment of the present disclosure. Graph 130 includesfirst data set 132, second data set 134, and third data set 136. Asshown in the illustrative embodiment of FIG. 3, graph 130 presents dataindicating analysis predications related to the capability of system 120to predict/determine/estimate a CO₂ fraction (i.e., amount orpercentage) in natural gas fuel that is presumed to have some quantityof methane. As illustratively shown, data set 132 shows that a zeropercent difference between sensor flow rate measurements provided bysensor 104, 105 indicates that no CO₂ fraction is present within thenatural gas fuel. Data set 134 shows that an approximately 45 percentdifference between sensor flow rate measurements provided by sensor 104,105 indicates a 0.5 CO₂ fraction is present within the natural gas fuel(i.e., fuel is 50% CO₂). Lastly, data set 136 shows that anapproximately 69 percent difference between sensor flow ratemeasurements provided by sensor 104, 105 indicates a 1.0 CO₂ fraction ispresent within the natural gas fuel (i.e., fuel is 100% CO₂).Accordingly, the sensor data shown in graph 130 indicates that system120 can be used to predict CO₂ fraction in natural gas fuels used tooperate a vehicle having engine 108 and system 120 disposed therein.

FIG. 4 is a graph 140 that correlates sensor data to mass flow rate fora plurality of fluid compositions 143 according to an embodiment of thepresent disclosure. More specifically, the sensor data of graph 140indicates that, for each fluid composition of the plurality of fluidcompositions 143, there is a corollary in terms of an expected percentdifference between sensors 104, 105 of system 120. Graph 140 includesfirst data set 138, second data set 139, third data set 141, and fourthdata set 142. Graph 140 further includes a graph key/legend 144 thatidentifies a particular fluid composition and its corresponding graphsymbol. As discussed above, in one embodiment, sensors 104, 105 arecalibrated to provide mass flow rate measurements for a fluidcomposition that is pure methane. Hence, because sensors 104, 105 arecalibrated for pure methane, each sensor will exhibit errors in flowrate measurements of natural gas fuel blended with constituents otherthan methane.

In the illustrative embodiment of FIG. 4, first data set 138 shows thata pure methane fuel/fluid composition measured by sensors 104, 105results in approximately 0% difference between the measured sensorvalues irrespective of total mass flow rate (as expected since sensorsare calibrated for methane). Second data set 139 includes data for twoseparate fluid compositions and shows that: 1) a fluid compositioncomprised of 50% methane and 50% propane results in approximately 8%difference between the measured sensor values irrespective of total massflow rate; and 2) a fluid composition comprised of 100% propane resultsin approximately 10% difference between the measured sensor valuesirrespective of total mass flow rate. Third data set 141 shows that afluid composition comprised of 50% methane and 50% carbon dioxideresults in approximately 45% difference between the measured sensorvalues irrespective of total mass flow rate. Fourth data set 142 showsthat a pure carbon dioxide fuel/fluid composition measured by sensors104, 105 results in approximately 70% difference between the measuredsensor values at 200 to 600 total mass flow rate measured in pound-massper hour (lb_(m)/hr). Fourth data set 142 further shows that, at 1000lb_(m)/hr to 1500 lb_(m)/hr, a pure carbon dioxide fuel/fluidcomposition measured by sensors 104, 105 results in approximately 68-69%difference between the measured sensor values.

In one embodiment, system 120 may be configured to detect/estimate apercentage of a first fluid type in the natural gas fuel when thepercent difference between the mass flow rate measurements provided bysensor 104 and sensor 105 exceeds a threshold percent difference. In oneaspect of this embodiment, the threshold percent difference is 10% andsystem 120 detects or estimates a percentage of carbon dioxide (i.e.,first fluid type) in the natural gas fuel based on the thresholddifference exceeding 10%. As indicated above, in one embodiment, sensor104 is a hot film mass flow sensor that operates, in part, based ondesign sensitivities which are responsive to the viscosity of the fluidbeing sensed, thermal conductivity of the fluid being sensed/measured,or both. Additionally, in this embodiment, sensor 105 is an orificedelta pressure mass flow rate measurement sensor that operates, in part,based on design sensitivities which are responsive to the molecularweight of the fluid being sensed. The illustrative embodiment of FIG. 4shows that sensors 104, 105 of system 120 indicate relatively largesensor differences for natural gas fuels blended with CO₂ and relativelysmall sensor differences for natural gas fuels blended with propaneblends. These differences are due, in part, to the fact that propane andcarbon dioxide have essentially the same molecular weight, so an orificedelta pressure measurement cannot tell the difference between them.However, because propane and CO₂ have very different viscosities, a hotfilm flow rate measurement will react to propane and CO₂ differently.Thus, as shown in FIG. 4, when two sensors, each operating based ondifferent principles, are used to sense/measure flow rate of anexemplary natural gas fuel, a percent difference in measured values willresult which then may be utilized to detect the presence of a particularfluid type in the natural gas fuel.

FIG. 5 is a block diagram of a fluid type prediction system comprisingat least three sensors according to an embodiment of the presentdisclosure. Flow measuring system 150 (hereinafter “system 150”)generally includes substantially the same components as system 120,except that system 150 includes first flow sensor 104, second flowsensor 105, and a third sensor 107. System 150 further includes firstestimation block 114, second estimation block 116, and third estimationblock 118. In one embodiment of the present disclosure, third sensor 107provides a measurement of a characteristic of a particular fluid/fuelwithin the natural gas fuel supplied to engine 108, wherein thecharacteristic indicates a percentage of a second fluid type in thefluid. In one aspect of this embodiment, the characteristic is thermalconductivity of one or more constituents that comprise the fluid beingsensed. In the illustrative embodiment of FIG. 5, third sensor 107 is anexemplary thermal sensor that measures the thermal conductivity of afluid supplied to engine 108. Much like sensors 104, 105 describedabove, thermal sensor 107 is configured to provide one or moredata/parameter signals to controller 203 that indicate thesensed/measured thermal conductivity of natural gas fuel used withinengine 108.

In one embodiment, system 150 operates in the following manner; flowrate of natural gas fuel supplied to engine 108 is sensed/measured bysensor 104 and sensor 105 and controller 203 receives one or moreparameter signals which indicate the flow rate value measured by thesensors. In this embodiment, memory M of controller 203 includeslogic/instructions in the form of executable code that when executed byprocessor P causes the controller 203 to detect a percent differencebetween a mass flow rate measurement provided by sensor 104 and a massflow rate measurement provided by second sensor 105. In the presentdisclosure, a certain percent difference will indicate the presence ofat least a first fluid type in the fluid, namely, carbon dioxide.Controller 203 may further include logic that causes the controller toestimate the percentage/fraction of the CO₂ in the natural gas fuelbased on or using the detected percent difference between the flow ratemeasurements provided by sensors 104 and sensor 105 (see estimationblock 114). As discussed briefly above, controller 203 may then provideone or more control signals to engine 108 to adjust at least oneperformance characteristic of engine 108 in response to detecting apresence of the first fluid type in the natural gas fuel, in response toestimating the percentage/fraction of the CO₂ in the fuel, and/or inresponse to detecting the percent difference between the mass flow ratemeasurement provided by first sensor 104 and the mass flow ratemeasurement provided by second sensor 105.

Additionally, during operation of system 150, controller 203 may furtherreceive one or more parameter signals indicating the thermalconductivity of one or more constituents that comprise the natural gasfuel. Likewise, in this embodiment, memory M of controller 203 includeslogic/instructions in the form of executable code that when executed byprocessor P causes the controller 203 to detect the presence of andestimate the percentage/fraction of a second fluid type in the naturalgas fuel based on or using the thermal conductivity measurement providedby second sensor 107 (see estimation block 116). More particularly, inthe present disclosure, a certain thermal conductivity value correspondsto a certain percentage/fraction of methane in natural gas fuel. Thus,as described in more detail in the disclosed embodiment of FIG. 6, ifthe natural gas fuel supplied to engine 108 is comprised of methane,then the thermal conductivity parameter value provided by sensor 107 maybe used to estimate the percentage/fraction of methane in the naturalgas fuel. In one embodiment, controller 203 may provide one or morecontrol signals to engine 108 to adjust at least one performancecharacteristic of engine 108 in response to detecting the presence ofand/or estimating the percentage/fraction of the second fluid type(e.g., methane—CH₄ fraction) in the natural gas fuel.

As discussed above, an exemplary natural gas fuel composition includesmethane, propane, and carbon dioxide. As also noted above, majorconstituent variations in the composition of natural gas fuels includechanges in the amount of methane, propane, and carbon dioxide present inthe fuel. In the illustrative embodiment of FIG. 5, estimation block 118provides a straightforward equation wherein the percentage of the firstfluid type (e.g., carbon dioxide—CO₂) and the percentage of the secondfluid type (e.g., methane—CH₄) are used to determine a presence of athird fluid type (e.g., propane—C₃H₈) in the natural gas fuel and todetermine or estimate a fraction/percentage of the third fluid type inthe natural gas fuel. Accordingly, in one embodiment, controller 203 mayfurther include logic that causes the controller to estimate thepercentage/fraction of the first fluid type and the second fluid typeand use these estimated fractions to determine a percentage/fraction ofa third fluid type by using the equation of estimation block 118.Accordingly, system 150 may be used to determine the natural gas fuelcomposition by estimating the percentage/fraction of at least threedistinct fluids that primarily comprise natural gas fuel. In oneembodiment, controller 203 may provide one or more control signals toengine 108 to adjust at least one performance characteristic of engine108 in response to determining the natural gas fuel composition byestimating the percentage/fraction of the at least three distinct fluidsthat primarily comprise natural gas fuel. In one aspect of thisembodiment, the performance characteristic includes, for example, fuelinjection timing, air-to-fuel ratio, charge flow rate and quantity,spark ignition timing, etc. In a variant of this aspect, adjusting theperformance characteristic of engine 108 may include adjusting theoperation of one or more components of engine 108.

FIG. 6 is a graph 160 that correlates sensor data to a second fluidpercentage according to an embodiment of the present disclosure. In theillustrative embodiment of FIG. 6, the sensor data is shown at Y-axis162 and corresponds to a range of thermal conductivity values (inmilliWatts per meters-Kelvin—(mW/(m-K)) that may be output by sensor 107when sensor 107 is a thermal conductivity sensor. Likewise, X-axis 164includes a range of second fluid percentage values that correspond tothe thermal conductivity values of Y-axis 162 when the second fluid ismethane—CH₄ gas. Propane (C₃H₈) and CO₂ have very similar thermalconductivity values, thus, for natural gas fuels that include somemixture of carbon dioxide and propane, a thermal conductivity sensorwill generally output substantially the same values for each of thesefluid types. As noted above, a certain thermal conductivity valuecorresponds to a certain percentage/fraction of methane—CH₄ in naturalgas fuel. Thus, if natural gas fuel supplied to engine 108 is comprisedof methane (in addition to C₃H₈ and CO₂), then the thermal conductivityparameter value provided by sensor 107 may be used to estimate thepercentage/fraction of methane in the natural gas fuel.

FIG. 7 is an exemplary flow diagram of a method 200 for predicting afluid type in an exemplary natural gas fuel according to an embodimentof the present disclosure. In various embodiments, method 200 may beimplemented and/or executed in a vehicle (or related engine applicationas described above) including at least one of system 120 and system 150.As such, a description of method 200 may reference the aforementionedcomponents of system 120 and 150. Method 200 begins at block 202 andincludes providing, by first sensor 104, a mass flow rate measurement ofa fluid in engine 108, wherein the first sensor 104 is sensitive to atleast a first property of the fluid. In one embodiment, the first fluidproperty may be at least one of the viscosity of the fluid and thethermal conductivity of the fluid. At block 204, method 200 furtherincludes providing, by second sensor 105, a mass flow rate measurementof the fluid, wherein second sensor 105 is sensitive to at least asecond property of the fluid. In one embodiment, the second fluidproperty may be the molecular weight of the fluid. At block 206, method200 further includes detecting, by a logic circuit of controller 203, adifference between the mass flow rate measurement provided by firstsensor 104 and second sensor 105, the difference indicating a presenceof at least a first fluid type in the fluid. Method 200 further includesblock 208 which detects a percentage of the first fluid type in thefluid when the difference in the mass flow measurement provided by firstsensor 104 and second sensor 105 exceeds a threshold difference. Atblock 210, method 200 includes sensing, by third sensor 107, acharacteristic of the fluid and detecting, based on the characteristic,the presence of at least a second fluid type in the fluid; anddetermining a percentage of the second fluid type in the fluid. In oneembodiment, the characteristic is the thermal conductivity of the fluidbeing sensed. At block 212, method 200 includes using the percentage ofthe first fluid type and the percentage of the second fluid type todetermine a presence of a third fluid type in the fluid and to determinea percentage of the third fluid type in the fluid.

As described herein, by analyzing mass flow rate measurements of deltapressure across an orifice and flow rate measurements from a hot filmmass flow sensor, one can estimate the carbon dioxide—CO₂ fraction innatural gas fuel. Moreover, through the use of a thermal conductivitysensor one can estimate the methane—CH₄ fraction. The remainder wouldthen be the propane—C₃H₈ fraction. The fluid detection and fractionestimation capabilities of systems 120 and 150 are achieved because theone or more sensors described herein have different sensitivities tomolecular weight, thermal conductivity, and viscosity relative to thefluid being measured. Accordingly, a combination of two mass flow ratemeasurement sensors and one thermal conductivity sensor can be utilizedto gain new information of natural gas fuel properties which allows forbetter control of an exemplary natural gas engine such as engine 108.

Through the teachings of the present disclosure, one of ordinary skillwill understand, based on the detected natural gas fuel composition,whether changes in engine knocking conditions are from a change in fueldiluent level (i.e., CO2 blended in the natural gas fuel) or hydrocarboncontent (i.e., propane blended in the natural gas fuel). With theadditional knowledge of why engine knock has changed, one can react withthe engine controls to improve engine performance and/or to adjust oneor more performance characteristics of engine 108. Propane for example,increases engine knock but also has a higher lean limit. With knowledgeof propane over less CO₂, one can operate the engine at leanerconditions to avoid or substantially mitigate the occurrence of engineknock. Moreover, since CO₂ is a diluent, similar to more fresh air 106or recirculated exhaust gas (i.e., EGR), it is very beneficial to knowhow much CO₂ is included in the fuel and if the CO₂ content changes thevehicle operator might react differently than if the propane levelchanged. Therefore, having reliable information which indicates naturalgas fuel composition and/or whether fuel quality is changing over time(or changing based on source location) is very useful for enginemanufacturers. In exemplary engine control and natural gas fuel systems,reliable detection of the fuel composition aids in engine performancesince optimal engine control and performance set points may be differentfor the diluent and hydrocarbon conditions.

It will be appreciated that some embodiments may be comprised of one ormore generic or specialized processors (or “processing devices”) such asmicroprocessors, digital signal processors, customized processors andfield programmable gate arrays (FPGAs) and unique stored programinstructions (including both software and firmware) that control the oneor more processors to implement, in conjunction with certainnon-processor circuits, some, most, or all of the functions of themethod and/or apparatus described herein. Alternatively, some or allfunctions could be implemented by a state machine that has no storedprogram instructions, or in one or more application specific integratedcircuits (ASICs), in which each function or some combinations of certainof the functions are implemented as custom logic. Of course, acombination of the two approaches could be used.

Moreover, an embodiment can be implemented as a computer-readablestorage medium having computer readable code stored thereon forprogramming a computer (e.g., comprising a processor) to perform amethod as described and claimed herein. Examples of suchcomputer-readable storage media include, but are not limited to, a harddisk, a CD-ROM, an optical storage device, a magnetic storage device, aROM (Read Only Memory), a PROM (Programmable Read Only Memory), an EPROM(Erasable Programmable Read Only Memory), an EEPROM (ElectricallyErasable Programmable Read Only Memory) and a Flash memory. Further, itis expected that one of ordinary skill, notwithstanding possiblysignificant effort and many design choices motivated by, for example,available time, current technology, and economic considerations, whenguided by the concepts and principles disclosed herein will be readilycapable of generating such software instructions and programs withminimal experimentation.

In the foregoing specification, specific embodiments of the presentdisclosure have been described. However, one of ordinary skill in theart will appreciate that various modifications and changes can be madewithout departing from the scope of the disclosure as set forth in theclaims below. Accordingly, the specification and figures are to beregarded in an illustrative rather than a restrictive sense. Thebenefits, advantages, solutions to problems, and any element(s) that maycause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as critical, required, or essentialfeatures or elements of any or all the claims. The invention is definedsolely by the appended claims including any amendments made during thependency of this application and all equivalents of those claims asissued. No claim element herein is to be construed under the provisionsof 35 U.S.C. 112(f) unless the element is expressly recited using thephrase “means for.”

We claim:
 1. A fluid type prediction system, comprising: a first sensorthat provides a first mass flow measurement of a fluid in an engine,wherein the first sensor is sensitive to at least a first property ofthe fluid; a second sensor that provides a second mass flow measurementof the fluid, wherein the second sensor is sensitive to at least asecond property of the fluid; and a controller configured to detect adifference between the first and the second mass flow measurementsindicating a presence of at least a first fluid type in the fluid, andto adjust a performance characteristic of the engine in response todetecting the difference between the first and second mass flowmeasurements; wherein the fluid is natural gas fuel, the first propertyis molecular weight, and the second property is at least one ofviscosity and thermal conductivity.
 2. The fluid type prediction systemof claim 1, wherein the system is configured to detect a percentage ofthe first fluid type in the fluid in response to the difference betweenthe first and second mass flow measurements exceeding a thresholddifference.
 3. The fluid type prediction system of claim 2, furthercomprising a third sensor that provides a measurement of acharacteristic of the fluid, wherein the characteristic indicates apercentage of a second fluid type in the fluid.
 4. The fluid typeprediction system of claim 3, wherein the percentage of the first fluidtype and the percentage of the second fluid type are used to determine apresence of a third fluid type in the fluid and to determine apercentage of the third fluid type in the fluid.
 5. The fluid typeprediction system of claim 3, wherein the first sensor is an orificedelta pressure mass flow sensor, the second sensor is a hot film massflow sensor, and the third sensor is a thermal conductivity sensor. 6.The fluid type prediction system of claim 3, wherein the fluid isnatural gas fuel comprising at least one of methane, propane, carbondioxide, and combinations thereof, and the characteristic of the fluidis a thermal conductivity of the fluid.
 7. The fluid type predictionsystem of claim 1, wherein the system is configured to estimate apercentage of one or more fluid types in the fluid.
 8. A fluid typeprediction system, comprising: a controller comprising at least oneprocessor and memory; and a first interface coupled to the controller,the first interface configured to receive parameter signalscorresponding to a mass flow measurement of a fluid in an engine, theparameter signals being provided by at least a first sensor and a secondsensor; wherein the memory comprises instructions that when executed bythe at least one processor causes the controller to detect a differencebetween the mass flow measurement provided by the first sensor and themass flow measurement provided by the second sensor, the differenceindicating the presence of at least a first fluid type in the fluid, andto adjust a performance characteristic of the engine in response todetecting the difference between the mass flow measurements provided bythe first and second sensors; and wherein the first interface receivesparameter signals provided by a third sensor, the parameter signalsindicating a characteristic of the fluid, wherein the characteristicindicates a percentage of a second fluid type in the fluid.
 9. The fluidtype prediction system of claim 8, wherein the system is configured todetect a percentage of the first fluid type in the fluid in response tothe difference between the mass flow measurements provided by the firstsensor and the second sensor exceeding a threshold difference.
 10. Thefluid type prediction system of claim 8, wherein the first sensor issensitive to at least a first property of the fluid and the secondsensor is sensitive to at least a second property of the fluid.
 11. Thefluid type prediction system of claim 8, wherein the controllercomprises a second interface configured to provide control signals to atleast the first sensor and the second sensor to cause the first andsecond sensors to provide the mass flow measurement to the controller.12. The fluid type prediction system of claim 10, wherein the fluid isnatural gas fuel, the first property is molecular weight, and the secondproperty is at least one of viscosity and thermal conductivity.
 13. Thefluid type prediction system of claim 8, wherein the controller uses thepercentage of the first fluid type and the percentage of the secondfluid type to determine a presence of a third fluid type in the fluidand to determine a percentage of the third fluid type in the fluid. 14.The fluid type prediction system of claim 8, wherein the first sensor isan orifice delta pressure mass flow sensor, the second sensor is a hotfilm mass flow sensor, and the third sensor is a thermal conductivitysensor.
 15. A method for predicting a fluid type, comprising: providing,by a first sensor, a mass flow measurement of a fluid in an engine,wherein the first sensor is sensitive to at least a first property ofthe fluid; providing, by a second sensor, a mass flow measurement of thefluid, wherein the second sensor is sensitive to at least a secondproperty of the fluid; detecting, by a logic circuit of a controller, adifference between the mass flow measurement provided by the firstsensor and the second sensor, the difference indicating a presence of atleast a first fluid type in the fluid; adjusting, by the logic circuit,a performance characteristic of the engine in response to detecting thedifference between the mass flow measurement provided by the firstsensor and the second sensor; detecting a percentage of the first fluidtype in the fluid in response to the difference in the mass flowmeasurement provided by the first sensor and the second sensor exceedinga threshold difference; and sensing, by a third sensor, a characteristicof the fluid; detecting, based on the characteristic, the presence of atleast a second fluid type in the fluid; and determining a percentage ofthe second fluid type in the fluid.
 16. The method of claim 15, furthercomprising using the percentage of the first fluid type and thepercentage of the second fluid type to determine a presence of a thirdfluid type in the fluid and to determine a percentage of the third fluidtype in the fluid.
 17. The method of claim 15, wherein the first sensoris an orifice delta pressure mass flow sensor, the second sensor is ahot film mass flow sensor, the third sensor is a thermal conductivitysensor, the first property is molecular weight, and the second propertyis at least one of viscosity and thermal conductivity.
 18. A fluid typeprediction system, comprising: a controller comprising at least oneprocessor and memory; and an interface coupled to the controller, theinterface configured to receive parameters indicating a mass flowmeasurement of a fluid in an engine; wherein the memory comprisesinstructions that when executed by the at least one processor causes thecontroller to detect a difference between the mass flow measurementprovided by a first sensor and the mass flow measurement provided by asecond sensor, the difference indicating the presence of at least afirst fluid type in the fluid; wherein a performance characteristic ofthe engine is adjusted in response to the controller detecting adifference between the mass flow measurements provided by the first andsecond sensors; wherein the parameters received by the interface areprovided by at least the first sensor and the second sensor; and whereinthe interface is further configured to receive a measurement of acharacteristic of the fluid, the characteristic indicating a percentageof a second fluid type in the fluid, and the measurement being providedby a third sensor.
 19. The fluid type prediction system of claim 18,wherein the first sensor is an orifice delta pressure mass flow sensor,the second sensor is a hot film mass flow sensor, and the third sensoris a thermal conductivity sensor.
 20. The fluid type prediction systemof claim 18, wherein the system is configured to at least one ofestimate a percentage of one or more fluid types in the fluid and detecta percentage of the first fluid type in the fluid in response to thedifference between the first and the second mass flow measurementsexceeding a threshold difference.
 21. The fluid type prediction systemof claim 18, wherein the performance characteristic includes at leastone of fuel injection timing, air-to-fuel ratio, charge flow rate andquantity, spark ignition timing, and adjusting the operation of one ormore components of the engine.
 22. A fluid type prediction system,comprising: a first sensor that provides a first mass flow measurementof a fluid in an engine, wherein the first sensor is sensitive to atleast a first property of the fluid; a second sensor that provides asecond mass flow measurement of the fluid, wherein the second sensor issensitive to at least a second property of the fluid; a third sensorthat provides a measurement of a characteristic of the fluid; and acontroller configured to detect a difference between the first and thesecond mass flow measurements, indicating a presence of at least a firstfluid type in the fluid, and to adjust a performance characteristic ofthe engine in response to detecting the difference between the first andsecond mass flow measurements; wherein the system is configured todetect a percentage of the first fluid type in the fluid in response tothe difference between the first and second mass flow measurementsexceeding a threshold difference; and wherein the characteristicindicates a percentage of a second fluid type in the fluid.
 23. Thefluid type prediction system of claim 22, wherein the percentage of thefirst fluid type and the percentage of the second fluid type are used todetermine a presence of a third fluid type in the fluid and to determinea percentage of the third fluid type in the fluid.
 24. The fluid typeprediction system of claim 22, wherein the first sensor is an orificedelta pressure mass flow sensor, the second sensor is a hot film massflow sensor, and the third sensor is a thermal conductivity sensor. 25.The fluid type prediction system of claim 22, wherein the fluid isnatural gas fuel comprising at least one of methane, propane, carbondioxide, and combinations thereof, and the characteristic of the fluidis a thermal conductivity of the fluid.
 26. A fluid type predictionsystem, comprising: a controller comprising at least one processor andmemory; and a first interface coupled to the controller, the firstinterface configured to receive parameter signals corresponding to amass flow measurement of a fluid in an engine, the parameter signalsbeing provided by at least a first sensor and a second sensor; whereinthe memory comprises instructions that when executed by the at least oneprocessor causes the controller to detect a difference between the massflow measurement provided by the first sensor and the mass flowmeasurement provided by the second sensor, the difference indicating thepresence of at least a first fluid type in the fluid, and to adjust aperformance characteristic of the engine in response to detecting thedifference between the mass flow measurements provided by the first andsecond sensors; wherein the first sensor is sensitive to at least afirst property of the fluid and the second sensor is sensitive to atleast a second property of the fluid; wherein the fluid is natural gasfuel, the first property is molecular weight, and the second property isat least one of viscosity and thermal conductivity.